Job request: 17035

Organisation:: Bennett Institute
Workspace:: the-impact-of-covid-19-on-prescribing-of-antimicrobials-interactive
ID:: u7u4g4ey2mecrudm

This page shows the technical details of what happened when the authorised researcher Brian MacKenna (PHC) requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level various outputs were written to. Researchers can never directly view outputs marked as highly_sensitive ; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

Action:

generate_study_population_ethnicity_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

g3m2w5ecwebmwybd
Action:

generate_study_population_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

wir4hostdhovm2yr
Action:

join_cohorts_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

e4ibpcfggd45v5ry
Action:

generate_measures_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

sgszxxwc67uufpuj
Action:

event_counts_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

prkcvhtma3v7p6go
Action:

plot_measure_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

nqahf5tksk7u7t7g
Action:

deciles_chart_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

is5guec6nw6aq7ri
Action:

top_5_table_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

htykdkuwx2pcmc5k
Action:

generate_report_01GXRGGBFB9PNT42F46VMJGHRA

Status:

Status: Succeeded

Job identifier:

aoizzh3nbyfuvstb

Pipeline

Show project.yaml

version: '3.0'

expectations:
  population_size: 1000

actions:

  generate_study_population_ethnicity_01GXRGGBFB9PNT42F46VMJGHRA:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_ethnicity
      --param end_date="2023-04-05"
      --output-dir output/01GXRGGBFB9PNT42F46VMJGHRA --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/01GXRGGBFB9PNT42F46VMJGHRA/input_ethnicity.csv.gz


  generate_study_population_01GXRGGBFB9PNT42F46VMJGHRA:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition
      --param codelist_1_path="interactive_codelists/codelist_1.csv"
      --param codelist_1_type="medication"
      --param codelist_2_path="interactive_codelists/codelist_2.csv"
      --param codelist_2_type="event"
      --param codelist_1_frequency="monthly"
      --param time_value="4"
      --param time_scale="weeks"
      --param time_event="before"
      --param codelist_2_comparison_date="end_date"
      --param operator="AND"
      --param population="adults"
      --param breakdowns="sex,age,ethnicity,imd,region"
      --index-date-range="2019-09-01 to 2023-04-05 by month"
      --output-dir=output/01GXRGGBFB9PNT42F46VMJGHRA
      --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/01GXRGGBFB9PNT42F46VMJGHRA/input_*.csv.gz

  join_cohorts_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      cohort-joiner:v0.0.38
        --lhs output/01GXRGGBFB9PNT42F46VMJGHRA/input_20*.csv.gz
        --rhs output/01GXRGGBFB9PNT42F46VMJGHRA/input_ethnicity.csv.gz
        --output-dir output/01GXRGGBFB9PNT42F46VMJGHRA/joined
    needs: [generate_study_population_01GXRGGBFB9PNT42F46VMJGHRA, generate_study_population_ethnicity_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      highly_sensitive:
        cohort: output/01GXRGGBFB9PNT42F46VMJGHRA/joined/input_20*.csv.gz

  generate_measures_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      python:latest -m analysis.measures
        --breakdowns="sex,age,ethnicity,imd,region"
        --input_dir="output/01GXRGGBFB9PNT42F46VMJGHRA/joined"
        --measure="med_review"

    needs: [join_cohorts_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      moderately_sensitive:
        measure: output/01GXRGGBFB9PNT42F46VMJGHRA/joined/measure*rate.csv
        decile_measure: output/01GXRGGBFB9PNT42F46VMJGHRA/joined/measure*rate_deciles.csv

  top_5_table_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      python:latest python analysis/top_5.py
      --codelist-1-path="interactive_codelists/codelist_1.csv"
      --codelist-2-path="interactive_codelists/codelist_2.csv"
      --output-dir="output/01GXRGGBFB9PNT42F46VMJGHRA"
    needs: [generate_measures_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      moderately_sensitive:
        tables: output/01GXRGGBFB9PNT42F46VMJGHRA/joined/top_5*.csv

  deciles_chart_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      deciles-charts:v0.0.33
        --input-files output/01GXRGGBFB9PNT42F46VMJGHRA/joined/measure_practice_rate_deciles.csv
        --output-dir output/01GXRGGBFB9PNT42F46VMJGHRA/joined
    config:
      show_outer_percentiles: true
      tables:
        output: true
      charts:
        output: true
    needs: [generate_measures_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      moderately_sensitive:
        deciles_charts: output/01GXRGGBFB9PNT42F46VMJGHRA/joined/deciles_*.*

  plot_measure_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      python:latest python analysis/plot_measures.py
        --breakdowns="sex,age,ethnicity,imd,region"
        --output-dir output/01GXRGGBFB9PNT42F46VMJGHRA
    needs: [generate_measures_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      moderately_sensitive:
        measure: output/01GXRGGBFB9PNT42F46VMJGHRA/plot_measure*.png

  event_counts_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      python:latest python analysis/event_counts.py --input_dir="output/01GXRGGBFB9PNT42F46VMJGHRA/joined" --output_dir="output/01GXRGGBFB9PNT42F46VMJGHRA"
    needs: [join_cohorts_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      moderately_sensitive:
        measure: output/01GXRGGBFB9PNT42F46VMJGHRA/event_counts.json

  generate_report_01GXRGGBFB9PNT42F46VMJGHRA:
    run: >
      python:latest python analysis/render_report.py
      --output-dir="output/01GXRGGBFB9PNT42F46VMJGHRA"
      --report-title="Doxycycline (tetracyclines) & Chronic obstructive pulmonary disease (COPD) codes"
      --population="adults"
      --breakdowns="sex,age,ethnicity,imd,region"
      --codelist-1-name="Doxycycline (tetracyclines)"
      --codelist-2-name="Chronic obstructive pulmonary disease (COPD) codes"
      --codelist-1-link="user/alexorlek/doxycycline-tetracyclines/4458c45a"
      --codelist-2-link="nhsd-primary-care-domain-refsets/copd_cod/20210127"
      --time-value="4"
      --time-scale="weeks"
      --time-event="before"
      --start-date="2019-09-01"
      --end-date="2023-04-05"
    needs: [event_counts_01GXRGGBFB9PNT42F46VMJGHRA, deciles_chart_01GXRGGBFB9PNT42F46VMJGHRA, top_5_table_01GXRGGBFB9PNT42F46VMJGHRA, plot_measure_01GXRGGBFB9PNT42F46VMJGHRA]
    outputs:
      moderately_sensitive:
        notebook: output/01GXRGGBFB9PNT42F46VMJGHRA/report.html

Timeline

Created: 1 year, 8 months ago 11 Apr 2023 15:56:17 UTC
Started: 1 year, 8 months ago 12 Apr 2023 07:10:55 UTC
Finished: 1 year, 8 months ago 14 Apr 2023 19:16:33 UTC
Runtime: 62:10:01

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status: Succeeded
Backend: TPP
Workspace: the-impact-of-covid-19-on-prescribing-of-antimicrobials-interactive
Requested by: Brian MacKenna (PHC)
Branch: main
Force run dependencies: Yes
Git commit hash: 9ba6826
Requested actions: run_all

Code comparison

Compare the code used in this Job Request

No previous Job Request available for comparison